Engaging communities in climate adaptation: the potential of social networks

There has been a growing recognition regarding the use of social networks to engage communities in government actions. However, despite increasing awareness of social networks, there is very limited evidence for their application in relation to climate policy. This study fills this gap by assessing the potential of social networks for engaging local communities in climate adaptation policy, drawing on a case study of the Shoalhaven region in Australia. Participants from key representative groups were recruited using a purposive snowball sampling technique (N?=?24). By mapping knowledge acquisition and diffusion networks in relation to climate adaption at the local scale, this study identified key nodes within the networks. Findings demonstrate that although climate adaptation information was acquired from a diverse range of sources, the sharing knowledge networks were far more dispersed. Furthermore, although 165 knowledge sources were identified, three nodes had coverage cross the entire network, and as such acted as boundary spanners within the sharing network. This research demonstrates the utility of social network analysis to reveal the underlying knowledge networks and structures that influence community engagement pathways and in doing so outlines key implications in relation to engaging local communities in climate policy and action.

Policy relevance

The rapid development of adaptation as a mainstream strategy for managing the risks of climate change has resulted in the emergence of a broad range of adaptation policies and management strategies globally. However, the success of these initiatives is largely dependent on their acceptance and uptake by local communities, which to date remains a significant challenge. Accordingly, policy makers require novel approaches to overcome barriers to community engagement so as to enhance the likely success of community engagement pathways. This article demonstrates the value of using social network analysis to reveal the underlying knowledge network structures. This approach makes it possible to identify key individuals within a community who can disseminate adaptation information quickly across broad geographic ranges. By utilizing this approach, policy makers globally will be able to increase the extent to which adaption initiatives are accepted and adhered to by local communities, thus increasing their success.